The complexity of structures, for example, used in oil and gas subsea exploration, is increasing to satisfy the many requirements in terms of thermal behaviour, geometry, multiple fluid flows, flexibility and mechanical characteristics. For example, some umbilicals or risers can be used to connect wells or facilities at the sea bed to, for example, floating facilities at the sea surface. Further examples of such structures include manifolds, separators and control units. It is desirable to monitor such connections in order to prevent structural failure due to fatigue, corrosion, erosion or blockage, which can be caused by the deposition of parts of the flow components (e.g., such as wax, hydrates, scales, asphaltenes, and the like).
Damage to such structures also can be due to human activity, such as fishing or laying and removal of anchors. Damage can also be the result of excessive stresses or shocks during transportation or deployment. Manufacturing defects can also compromise the quality of such structures.
For such reasons, leaks can develop in localized parts of such structures. Often such a leak is detected after it has become large, leading to unplanned repairs that can take a long time, as equipment, material and personnel need to be mobilized on short notice. Locating the leak is also an important issue. Sometimes the leak cannot be located with a simple visual inspection, requiring the replacement of long sections of the structure. For example, leaks can be of seawater into the structure, which can promote problems, such as corrosion or contamination of hydraulic lines, or leakage of oil or gas out of the structure.
Leakage detection in pipelines is of ever-increasing importance especially with environment and ecological concerns. In addition, from the point of view of the operator, there are severe consequences for a company's reputation resulting from a leak, and indeed potential liabilities.
Broadly speaking, leakage detection systems can be classified into two groups: hardware-based methods and software-based methods. Hardware-based methods are generally those with dedicated sensors, which respond directly to the existence of a leak. Specific examples are optical or semiconductor gas detectors, e.g., ‘sniffers’, acoustic sensors or DTS (Distributed Temperature Sensors), DSTS (Distributed Strain and Temperature Sensor) and DVS (Distributed Vibration Sensor), which is also referred to as CRN (Coherent Rayleigh Noise), its underlying technology, or as DAS (Distributed Acoustic Sensing) technologies. A DSTS is based on Brillouin scattering where a frequency shift of 10-12 GHz at an optical probe wavelength of 1550 nanometers is temperature and strain sensitive.
Two earlier patent applications: U.S. Patent Application No. 60/990,147 filed on 26 Nov. 2007 (which is a priority application of WO/2009/070769) and GB Patent Application No. GB0811705.3 filed on 26 Jun. 2008, disclose DTS type measurements.
U.S. 60/990,147 is concerned with a leak detection system having a sensor placed in a space defined between a first barrier to a first fluid and a second barrier to a second fluid. The sensor is used to detect the presence of the first or second fluid in the space due to a leak in the respective first or second barrier. If a leak is detected a signal is generated.
GB0811705.3 is concerned with improving the accuracy of the fluid leak detection of U.S. 60/990,147 by having a fibre optic sensor configured to measure an acoustic emission, wherein a fluid leak produces the acoustic emission. The system is configured to estimate the orifice diameter of the fluid leak based on the measured one or more characteristics and to calculate a leak rate based on the estimated orifice diameter.
Software-based methods normally consist of software packages using a combination of inputs from discrete sensors at various positions along a pipeline, for example provided by a SCADA (Supervisory Control & Data Acquisition) system. Specific examples are flow/pressure change detection, computational mass balance and pressure point analysis.
A disadvantage of such software-based methods is that they are also typically reliant on data from discrete sensors for monitoring pipeline parameters such as flow, temperature and pressure. In such systems, typically assumptions of uniformity along a pipeline, particularly of temperature, are needed. However, any deviations from such assumed uniformity can lead to errors.
Moreover, certain software-based techniques such as the mass-volume type method rely on measuring the difference in volume between the fluid input to the pipe and the output from the pipe to determine the leakage rate of flow. However, the temperature along the length of the pipe is likely to vary, particularly for exceptionally long pieces of pipeline passing through different environments, and known techniques do not accurately account for such variations.
Accordingly, there exists a need in the art to overcome the deficiencies and limitations described hereinabove.